Ball detection and tracking may be significant for semantics, team activity, and tactics analysis in broadcast soccer video. Most previous work used traditional object tracking algorithms, such as Kalman filters, template matching, particle filters, and so on, to handle this problem. However, there may be some difficulties with these approaches: (1) the ball is small and does not have stable or discriminative characteristics; (2) there is much noise, for example, region blobs, player parts, line-marks, etc; (3) occlusion; and (4) camera motion and shot transition.
Thus, there is a continuing need for a ball detection and tracking mechanism that overcomes the shortcomings of the prior art.